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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

SPC-70773 Rev 0 MARVEL Central Insurance Absorber Gray Rod Build to Print Specification

A. Idaho National Laboratory (INL) is developing a microreactor to produce electrical power utilizing a small nuclear core and Stirling engines under the Microreactor Application Research Validation and Evaluation (MARVEL) program. This procurement specification defines the requirements for fabrication of the Central Insurance Absorber Structure (CIAS) Gray Rod (Hafnium). B. Any conflict between this specification and referenced Codes and Standards, or any supplementary specifications in the procurement documents requires written clarification from the Contractor prior to proceeding with any work. Any deviation from the procurement documents requires approval by the Contractor with the change request process.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2023

SPC-70774 Rev 0 MARVEL Black Rod B4C Pellets Print Fabrication Specification

A. Idaho National Laboratory (INL) is developing a microreactor to produce electrical power utilizing a small nuclear core and Stirling engines under the Microreactor Application Research Validation and Evaluation (MARVEL) program. This procurement specification defines the requirements for fabrication of the MARVEL Black Rod B4C pellets. B. Any conflict between this specification and referenced Codes and Standards, or any supplementary specifications in the procurement documents requires written clarification from the Contractor prior to proceeding with any work. Any deviation from the procurement documents requires approval by the Contractor with the change request process.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

SPC-70796 Rev 2 MetCar M-312 Bearings Procurement Specification

A. Idaho National Laboratory (INL) is developing a microreactor to produce electrical power utilizing a small nuclear core under the Microreactor Application Research Validation and Evaluation (MARVEL) program. This procurement specification defines the requirements for fabrication of the MARVEL MetCar M-312 bearings. B. Any conflict between this specification and referenced Codes and Standards, or any supplementary specifications in the procurement documents requires written clarification from the Contractor prior to proceeding with any work. Any deviation from the procurement documents requires approval by the Contractor with the change request process.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2021

Programmable Site‐Specific Functionalization of DNA Origami with Polynucleotide Brushes

Abstract Combining surface‐initiated, TdT (terminal deoxynucleotidyl transferase) catalyzed enzymatic polymerization (SI‐TcEP) with precisely engineered DNA origami nanostructures (DONs) presents an innovative pathway for the generation of stable, polynucleotide brush‐functionalized DNA nanostructures. We demonstrate that SI‐TcEP can site‐specifically pattern DONs with brushes containing both natural and non‐natural nucleotides. The brush functionalization can be precisely controlled in terms of the location of initiation sites on the origami core and the brush height and composition. Coarse‐grained simulations predict the conformation of the brush‐functionalized DONs that agree well with the experimentally observed morphologies. We find that polynucleotide brush‐functionalization increases the nuclease resistance of DONs significantly, and that this stability can be spatially programmed through the site‐specific growth of polynucleotide brushes. The ability to site‐specifically decorate DONs with brushes of natural and non‐natural nucleotides provides access to a large range of functionalized DON architectures that would allow for further supramolecular assembly, and for potential applications in smart nanoscale delivery systems.

Yang, Yunqi↗
DOE OSTI2021

Programmable Site-Specific Functionalization of DNA Origami with Polynucleotide Brushes

Combining surface-initiated, TdT (terminal deoxynucleotidyl transferase) catalyzed enzymatic polymerization (SI-TcEP) with precisely engineered DNA origami nanostructures (DONs) presents an innovative pathway for the generation of stable, polynucleotide brush-functionalized DNA nanostructures. Here we demonstrate that SI-TcEP can site-specifically pattern DONs with brushes containing both natural and non-natural nucleotides. The brush functionalization can be precisely controlled in terms of the location of initiation sites on the origami core and the brush height and composition. Coarse-grained simulations predict the conformation of the brush-functionalized DONs that agree well with the experimentally observed morphologies. We find that polynucleotide brush-functionalization increases the nuclease resistance of DONs significantly, and that this stability can be spatially programmed through the site-specific growth of polynucleotide brushes. The ability to site-specifically decorate DONs with brushes of natural and non-natural nucleotides provides access to a large range of functionalized DON architectures that would allow for further supramolecular assembly, and for potential applications in smart nanoscale delivery systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Specificity determinants revealed by the structure of glycosyltransferase Campylobacter concisus PglA

Abstract In selected Campylobacter species, the biosynthesis of N‐linked glycoconjugates via the pgl pathway is essential for pathogenicity and survival. However, most of the membrane‐associated GT‐B fold glycosyltransferases responsible for diversifying glycans in this pathway have not been structurally characterized which hinders the understanding of the structural factors that govern substrate specificity and prediction of resulting glycan composition. Herein, we report the 1.8 Å resolution structure of Campylobacter concisus PglA, the glycosyltransferase responsible for the transfer of N ‐acetylgalatosamine (GalNAc) from uridine 5′‐diphospho‐ N ‐acetylgalactosamine (UDP‐GalNAc) to undecaprenyl‐diphospho‐ N , N ′‐diacetylbacillosamine (UndPP‐diNAcBac) in complex with the sugar donor GalNAc. This study identifies distinguishing characteristics that set PglA apart within the GT4 enzyme family. Computational docking of the structure in the membrane in comparison to homologs points to differences in interactions with the membrane‐embedded acceptor and the structural analysis of the complex together with bioinformatics and site‐directed mutagenesis identifies donor sugar binding motifs. Notably, E113, conserved solely among PglA enzymes, forms a hydrogen bond with the GalNAc C6″‐OH. Mutagenesis of E113 reveals activity consistent with this role in substrate binding, rather than stabilization of the oxocarbenium ion transition state, a function sometimes ascribed to the corresponding residue in GT4 homologs. The bioinformatic analyses reveal a substrate‐specificity motif, showing that Pro281 in a substrate binding loop of PglA directs configurational preference for GalNAc over GlcNAc. This proline is replaced by a conformationally flexible glycine, even in distant homologs, which favor substrates with the same stereochemistry at C4, such as glucose. The signature loop is conserved across all Campylobacter PglA enzymes, emphasizing its importance in substrate specificity.

Vuksanovic, Nemanja↗
DOE OSTI2025

The structural basis for the broad aldehyde specificity of the aminoaldehyde dehydrogenase PauC from the human pathogen Pseudomonas aeruginosa

Abstract Despite significant differences in size and formal charge, the aldehyde dehydrogenasePaPauC (PA5312) fromPseudomonas aeruginosaPAO1 efficiently catalyzes the NAD + ‐dependent oxidation of the aminoaldehydes formed in polyamines degradation. We report here thatPaPauC also oxidizes 4‐guanidinebutyraldehyde, formed in one arginine degradation pathway, trimethylaminobutyraldehyde, of unknown metabolic origin, and indole‐3‐acetaldehyde, a precursor of the plant growth‐promoting hormone indoleacetic acid.PaPauC has been proposed as a potential target for combatingP. aeruginosa. However, understanding its structure–function relationships, crucial for developing specific inhibitors, is lacking. Using X‐ray crystallography, we identified the structural characteristics that determinePaPauC broad aldehyde specificity: a spacious aldehyde‐entrance tunnel and six active‐site residues. Docking simulations, site‐directed mutagenesis, and kinetic analyses support the interactions of Lys479 with glutamylated aminoaldehydes; Phe169, Trp176, and Phe467 with amino and guanidinium groups through cation–π interactions and with the indole group via NH–π and CH–π interactions; Asp459 with amino and indole groups; and Thr303 with amide and guanidinium groups. Exploiting the distinctive structural features of thePaPauC active site could aid in developing specific inhibitors to combatP. aeruginosainfections in humans and animals, as well as in preventing its colonization of plants, which are abundantP. aeruginosareservoirs and, therefore, a significant source of human infections.

Biochemistry & Molecular Biology↗
DOE OSTI2022

COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry

The computational power increases over the past decades have greatly enhanced the ability to simulate chemical reactions and understand ever more complex transformations. Tensor contractions are the fundamental computational building block of these simulations. These simulations have often been tied to one platform and restricted in generality by the interface provided to the user. The expanding prevalence of accelerators and researcher demands necessitate a more general approach which is not tied to specific hardware or requires contortion of algorithms to specific hardware platforms. In this paper we present COMET, a domain-specific programming language and compiler infrastructure for tensor contractions targeting heterogeneous accelerators. We present a system of progressive lowering through multiple layers of abstraction and optimization that achieves up to 1.98×speedup for 30 tensor contractions commonly used in computational chemistry and beyond.

Mutlu, Erdal↗
DOE OSTI2022

Domain-Specific Type-Safe APIs for Hierarchical Scientific Data with Modern C++

General-purpose library application programming interfaces (APIs) for self-describing hierarchical scientific data storage, such as the HDF5 and NetCDF libraries, are traditionally of runtime nature. Runtime errors for entry existence and data types are typically caught later in the development process of higher-level application-specific APIs. In this paper, we propose exploiting modern C++ metaprogramming features to add compile-time type-safety to improve the interaction with a well-defined metadata-rich scientific schema in domain-specific hierarchical datasets. We tackle two aspects of common use: (i) direct data access, (ii) flexible “in-memory” index models for efficient search and data processing. The proposed APIs use C++17’s template type auto deduction features, C++11’s enum class for type-safety and C-style preprocessor macros for generative templated code. We showcase the pros and cons of our initial work on the standard NeXus schema used for annotating and storing experimental neutron scattering data at several facilities around the world on top of HDF5. Extendable compile-time type-safe APIs are a desirable feature that could be indexed by any modern integrated development environment (IDE). Hence, such APIs can help ease the learning curve for domain scientists using a less error-prone software interaction to enhance the findability of their data without resorting to a domain-specific language (DSL).

Godoy, William↗
DOE OSTI2021

Analysis-Specific Fast Simulation at the LHC with Deep Learning

Abstract We present a fast-simulation application based on a deep neural network, designed to create large analysis-specific datasets. Taking as an example the generation of W + jet events produced in $$\sqrt{s}=$$ s = 13 TeV proton–proton collisions, we train a neural network to model detector resolution effects as a transfer function acting on an analysis-specific set of relevant features, computed at generation level, i.e., in absence of detector effects. Based on this model, we propose a novel fast-simulation workflow that starts from a large amount of generator-level events to deliver large analysis-specific samples. The adoption of this approach would result in about an order-of-magnitude reduction in computing and storage requirements for the collision simulation workflow. This strategy could help the high energy physics community to face the computing challenges of the future High-Luminosity LHC.

Chen, C.↗
DOE OSTI2022

Application-specific optimal model weighting of global climate models: A red tide example

Global climate models (GCMs) and Earth system models (ESMs) provide many climate services with environmental relevance. The High Resolution Model Inter-comparison Project (HighResMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) provides model runs of GCMs and ESMs to address regional phenomena. Developing a parsimonious ensemble of CMIP6 requires multiple ensemble methods such as independent-model subset selection, prescreening-based subset selection, and model weighting. The work presented here focuses on application-specific optimal model weighting, with prescreening-based subset selection. As such, independent ensemble members are categorized, selected, and weighted based on their ability to reproduce physically-interpretable features of interest that are problem-specific. We discuss the strengths and caveats of optimal model weighting using a case study of red tide prediction in the Gulf of Mexico along the West Florida Shelf. Red tide is a common name of specific harmful algal blooms that occur worldwide, causing adverse socioeconomic and environmental impacts. Our results indicate the importance of prescreening-based subset selection as optimal model weighting can underplay robust ensemble members by optimizing error cancellation. Prescreening-based subset selection also provides insights about the validity of the model weights. By illustrating the caveats of using non-representative models when optimal model weighting is used, the findings and discussion of this study are pertinent to many other climate services.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Bridging semantics, control specifications and assessment: A library for scalable demand flexibility controls

There is growing recognition that Demand Flexibility (DF) can play a major role in enhancing grid reliability, with building control applications emerging as key enablers for DF. However, the traditional approach to deploying new control applications in buildings, including those for DF, remains largely manual and tailored to individual buildings, making it difficult to scale. While research efforts have explored semantics-driven portability, DF controls specification, and assessment approaches, these initiatives are fragmented and limited in scope. This paper proposes a novel methodology, grounded in design science research, to integrate these elements and create a comprehensive DF controls library for both industry and academia. This approach is applied to develop the Demand FLEXibility controls LIBrary using Semantics (DFLEXLIBS), an extensible open-source library that provides DF controls for HVAC systems in Python. DFLEXLIBS enables portable, easy-to-deploy controls that abstract building-specific data points, facilitating assessment across diverse buildings. DFLEXLIBS features nine different control applications, and it is successfully implemented and tested across four virtual and two real buildings, bridging the gap between semantics-driven portability, DF controls specification, and rigorous performance assessment. Its benefits are measured by a reusability ratio greater than 90% and a functional overlap ratio of around 70% for the most common functions used in the library, significantly reducing time for deploying new controls.

Controls library↗
DOE OSTI2025

An open control sequence specification to scale building demand flexibility via analytics software

For over two decades, researchers and practitioners have showcased the ability of large commercial buildings to provide grid services by shedding or shifting load. Various utility demand response (DR) and virtual power plant (VPP) programs throughout the United States are presently utilizing these demand-side resources. However, growth of these programs have been limited, in part due to the high cost necessary to integrate the DR control strategies into the building automation system (BAS). Implementing these strategies involves adjusting control sequences, necessitating dozens of hours of customized programming per building, limiting their adoption to large organizations and progressive owners. Recent efforts by researchers and industry have demonstrated the capability of energy management and information systems (EMIS), originally designed for fault detection and diagnostics, to interface with existing BAS and perform supervisory control to optimize building operations. While these approaches are quickly being adopted by industry, demand flexibility (DF) control strategies remain limited in product offerings. One of the challenges is the lack of documented best-practice DF sequences, despite the rich literature on field implementations. This paper develops a new open-specification for a zone-based temperature adjustment shed strategy for commercial building HVAC systems, describing the specification’s implementation in two EMIS tools in both experimental and field settings. Both implementations successfully reduced electric load by at least 40% on average during the called event, while maintaining temperature limits. This study’s detailed process from specification to deployment shows the potential for scalability as well as highlights challenges related to integration with heterogeneous BAS products.

Granderson, Jessica↗
DOE OSTI2022

Product specific thermal degradation kinetics of bisphenol F epoxy in inert and oxidative atmospheres using evolved gas analysis–mass spectrometry

Knowledge of the degradation kinetics for polymer materials is important for understanding thermal stability. In this study, evolved gas analysis–mass spectrometry and pyrolysis gas-chromatography-mass spectrometry were evaluated for the potential to deliver additional insight into thermal degradation kinetics of diglycidal ether of bisphenol F (DGEBF) epoxy thermoset under inert and oxidative atmospheres. Degradation products of selected precursor ions were evaluated for their uniqueness to the specific precursor using extracted ion thermographs. Unique mass peaks, solely attributed to a single reaction pathway of a specific product, were determined from extracted ion thermographs and used to determine both activation energy (E a ) and pre-exponential factors for the specific primary reaction pathways. These primary reaction pathways for DGEBF epoxy degradation were then evaluated in the context of transition state theory (TST) and related transition state enthalpies (ΔH ‡ ) and entropies (ΔS ‡ ) of activation to further elucidate the degradation process. It was determined under pyrolysis conditions, as suggested by the E a , the formation of bisphenol F monomer was the rate-limiting step toward the formation of xanthene and phenol. In contrast, under thermo-oxidative conditions, reactions involving oxygen containing species were identified as the rate-limiting step for all observed products based on the large negative ΔS ‡ calculated from TST. This work demonstrates a powerful combination of technique and theory that can provide new insight into the degradation of polymer materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Subject-specific modeling framework for particle deposition using computational fluid dynamics

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

AI↗
DOE OSTI2024

The crystal structure of Grindelia robusta 7,13-copalyl diphosphate synthase reveals active site features controlling catalytic specificity

Diterpenoid natural products serve critical functions in plant development and ecological adaptation and many diterpenoids have economic value as bioproducts. The family of class II diterpene synthases catalyzes the committed reactions in diterpenoid biosynthesis, converting a common geranylgeranyl diphosphate precursor into different bicyclic prenyl diphosphate scaffolds. Enzymatic rearrangement and modification of these precursors generate the diversity of bioactive diterpenoids. We report the crystal structure of Grindelia robusta 7,13-copalyl diphosphate synthase, GrTPS2, at 2.1 Å of resolution. GrTPS2 catalyzes the committed reaction in the biosynthesis of grindelic acid, which represents the signature metabolite in species of gumweed (Grindelia spp., Asteraceae). Grindelic acid has been explored as a potential source for drug leads and biofuel production. The GrTPS2 crystal structure adopts the conserved three-domain fold of class II diterpene synthases featuring a functional active site in the γβ-domain and a vestigial α-domain. Substrate docking into the active site of the GrTPS2 apo protein structure predicted catalytic amino acids. Biochemical characterization of protein variants identified residues with impact on enzyme activity and catalytic specificity. Specifically, mutagenesis of Y457 provided mechanistic insight into the position-specific deprotonation of the intermediary carbocation to form the characteristic 7,13 double bond of 7,13-copalyl diphosphate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

BIPSPI+: Mining Type-Specific Datasets of Protein Complexes to Improve Protein Binding Site Prediction

Computational approaches for predicting protein-protein interfaces are extremely useful for understanding and modelling the quaternary structure of protein assemblies. In particular, partner-specific binding site prediction methods allow delineating the specific residues that compose the interface of protein complexes. In recent years, new machine learning and other algorithmic approaches have been proposed to solve this problem. However, little effort has been made in finding better training datasets to improve the performance of these methods. With the aim of vindicating the importance of the training set compilation procedure, in this work we present BIPSPI+, a new version of our original server trained on carefully curated datasets that outperforms our original predictor. We show how prediction performance can be improved by selecting specific datasets that better describe particular types of protein interactions and interfaces (e.g. homo/hetero). In addition, our upgraded web server offers a new set of functionalities such as the sequence-structure prediction mode, hetero- or homo-complex specialization and the guided docking tool that allows to compute 3D quaternary structure poses using the predicted interfaces. BIPSPI+ is freely available at https://bipspi.cnb.csic.es.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

On the in-plane vibrations and electromechanical resonance characteristics of non-uniformly polarized rectangular piezoelectric wafers: Selective mode-type excitation and specific mode enhancement

Here, we investigate the in-plane vibrations and electromechanical resonance characteristics of non-uniformly polarized rectangular piezoelectric wafers. Non-uniform polarization is represented as a non-uniform electromechanical coupling coefficient using a polarization function. Governing equations are derived for the forced in-plane vibrations of a thin wafer under the assumption of generalized plane stress. The effect of non-uniform polarization is explicitly obtained in the forcing terms of the governing equations. These equations are then recast into a variational weak form that is then solved using the finite element method to obtain the displacement fields for different modes. The electromechanical response of a non-uniformly polarized piezoelectric wafer is derived in terms of the out-of-plane displacement profile on the surface of the wafer. Using the derived analytical expression, a necessary and sufficient condition for the presence/absence of a vibrational mode in the electromechanical impedance spectrum is obtained. Based on this condition, criteria for selective mode-type excitation and specific mode enhancement of vibrational modes in the electromechanical impedance spectrum are postulated. Selective mode-type excitation of in-plane extensional and shear modes is demonstrated for a square wafer and that of in-plane bending modes is demonstrated for a rectangular wafer. Specific mode enhancement is demonstrated for both square and rectangular wafers. In addition, it is also demonstrated how the criteria can be used to suppress specific vibrational modes in the electromechanical impedance spectrum. The proposed methodology of using non-uniformly polarized piezoelectric wafers finds application in the design of single element transducers with multi-frequency operation, frequency-tuned receivers/sensors, acoustic holograms, designing acoustic beams of prescribed shape/lobes, and other non-traditional applications such as information storage.

36 MATERIALS SCIENCE↗